Endocrinology

Latest AI and machine learning research in endocrinology for healthcare professionals.

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A Self-Supervised Equivariant Refinement Classification Network for Diabetic Retinopathy Classification.

Diabetic retinopathy (DR) is a retinal disease caused by diabetes. If there is no intervention, it m...

Children Are Not Small Adults: Addressing Limited Generalizability of an Adult Deep Learning CT Organ Segmentation Model to the Pediatric Population.

Deep learning (DL) tools developed on adult data sets may not generalize well to pediatric patients,...

Predicting Antidiabetic Peptide Activity: A Machine Learning Perspective on Type 1 and Type 2 Diabetes.

Diabetes mellitus (DM) presents a critical global health challenge, characterized by persistent hype...

Machine Learning-Driven discovery of immunogenic cell Death-Related biomarkers and molecular classification for diabetic ulcers.

In this study, we redefine the diagnostic landscape of diabetic ulcers (DUs), a major diabetes compl...

A natural language processing-informed adrenal gland incidentaloma clinic improves guideline-based care.

INTRODUCTION: Adrenal gland incidentalomas (AGIs) are found in up to 5% of cross-sectional images. H...

Prediction of gestational diabetes mellitus by multiple biomarkers at early gestation.

BACKGROUND: It remains unclear which early gestational biomarkers can be used in predicting later de...

Predicting hypoglycemia in ICU patients: a machine learning approach.

BACKGROUND: The current study sets out to develop and validate a robust machine-learning model utili...

Gluconeogenesis unraveled: A proteomic Odyssey with machine learning.

The metabolic pathway known as gluconeogenesis, which produces glucose from non-carbohydrate substra...

An attentional mechanism model for segmenting multiple lesion regions in the diabetic retina.

Diabetic retinopathy (DR), a leading cause of blindness in diabetic patients, necessitates the preci...

Novel artificial intelligence for diabetic retinopathy and diabetic macular edema: what is new in 2024?

PURPOSE OF REVIEW: Given the increasing global burden of diabetic retinopathy and the rapid advancem...

The utility of a machine learning model in identifying people at high risk of type 2 diabetes mellitus.

BACKGROUND: According to previous reports, very high percentages of individuals in Saudi Arabia are ...

Evaluation of AI-enhanced non-mydriatic fundus photography for diabetic retinopathy screening.

OBJECTIVE: To assess the feasibility of using non-mydriatic fundus photography in conjunction with a...

Development and validation of a machine learning-based approach to identify high-risk diabetic cardiomyopathy phenotype.

AIMS: Abnormalities in specific echocardiographic parameters and cardiac biomarkers have been report...

Precision meets generalization: Enhancing brain tumor classification via pretrained DenseNet with global average pooling and hyperparameter tuning.

Brain tumors pose significant global health concerns due to their high mortality rates and limited t...

Integrating Laser-Induced Breakdown Spectroscopy and Ensemble Learning as Minimally Invasive Optical Screening for Diabetes.

Diabetes mellitus is a prevalent chronic disease necessitating timely identification for effective m...

Comparison review of image classification techniques for early diagnosis of diabetic retinopathy.

Diabetic retinopathy (DR) is one of the leading causes of vision loss in adults and is one of the de...

Metabolic syndrome predictive modelling in Bangladesh applying machine learning approach.

Metabolic syndrome (MetS) is a cluster of interconnected metabolic risk factors, including abdominal...

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